Typically, the magnitude and power measurements of an electrical signal are expressed in terms of RMS (Root Mean Square) values since the algorithms for implementing such measurements are computationally inexpensive and analytically well understood. However, RMS measurements are sensitive to the distribution of values in the input data set, in particular, large-magnitude outliers. As a result, RMS measurements are strongly affected by spectral coloration and contamination.
In the context of wireless networking, this means that RMS Received Signal Strength Indications (RSSI) are skewed by channel filter shape, channel interference and noise. Root Median Square (RMedS) measurements are known to be less sensitive to outliers than RMS measurements. However, the algorithms for implementing RMedS measurements tend to be computationally expensive. Due to the limited computational power of a wireless mobile station, it is impractical to calculate the RSSI of a wireless signal at a mobile station using a conventional RMedS algorithm.
As a result, there remains a need for a method of estimating an electrical characteristic (e.g. voltage magnitude, current magnitude, or power) of an electrical signal that may be subjected to spectral coloration and contamination. There also remains a need for a method of estimating the RSSI of a wireless signal at a mobile station.